Disability Risk in Work-Related Musculoskeletal Injury

与工作相关的肌肉骨骼损伤的残疾风险

• 批准号: 6778225
• 负责人: GARY M. FRANKLIN
• 金额: $ 25.22万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-30 至 2006-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6778225
• 关键词: back injury; behavioral /social science research tag; carpal tunnel syndrome; clinical research; disability insurance; disease /disorder proneness /risk; employment /unemployment; functional ability; health related legal; human subject; injury prevention; interview; longitudinal human study; mathematical model; model design /development; occupational health /safety; questionnaires; social psychology; socioeconomics

DESCRIPTION: The vast majority of cost and lost productivity in workers' compensation is due to work related --musculoskeletal injuries. Among injured workers with these conditions, a small proportion (5-10 percent) develops long-term disability and account for most (80-85 percent) of the cost and lost work. In the absence of an accurate method to identify workers at risk for long-term disability, secondary prevention efforts cannot be well targeted. This is a 5-year, population-based, prospective study among Washington State workers with back injuries and carpal tunnel syndrome (CTS). The principal aim is to develop an accurate predictive model of risk for long-term disability among 5 key risk dimensions: employment related factors; biomedical healthcare related factors; socio-demographic factors; administrative/legal factors; and psychosocial factors. To accomplish this aim, a baseline interview among approximately 3000 eligible workers will be conducted within 2-6 weeks of (workers compensation) claim allowance. A continuous measure of disability outcome (lost time compensation) will be determined from a computerized database at one year. Additional important outcomes will be determined by a follow-up interview at one year (functional status, work status) and from computerized records (work status, wage status). Multivariate survival analysis within and across risk dimensions will be used to develop the principal risk models, including adjustment for injury severity. The reliability of determining severity from medical records will be determined as well (Specific Aim 2). A third aim of this study is to develop a brief risk assessment instrument for both low back and CTS injuries which would be useful to physicians when first treating injured workers. The main focus of these instruments would be on those risk factors which may be modifiable and which may be amenable to early intervention to prevent disability. Statistical analysis for this aim will focus on sensitivity and specificity of specific combinations of risk factors. These risk assessment instruments will be pilot tested among physicians participating in an occupational health care quality improvement project. The fourth aim of this project is to determine reinjury rate and predictors of reinjury among the original low back injury cohort 2 years after the initial injury. The unique study environment in Washington state, including the ability to conduct population-based sampling, timely access to survey injured workers, linkage of medical, claims and work status databases, and support from the business and labor communities, will substantially contribute to the success of this study.

描述：绝大多数的成本和工人的生产力损失 补偿是由于与工作有关的-肌肉骨骼伤害。受伤者中 有这些条件的工人，一小部分（5 - 10%）发展 长期残疾和占大多数（80 - 85%）的成本和损失 工作由于缺乏准确的方法来确定工人的风险， 长期残疾，二级预防工作不能很好地针对性。 这是一项在华盛顿州开展的为期5年、基于人群的前瞻性研究 背部受伤和腕管综合征（CTS）的工人。主要目的 是建立一个准确的长期残疾风险预测模型 在5个主要风险维度中：就业相关因素;生物医学保健 相关因素;社会人口因素;行政/法律的因素;以及 心理社会因素。为了实现这一目标，在 大约3000名合格工人将在2 - 6周内进行 （工人赔偿）索赔津贴。残疾的持续衡量 结果（损失的时间补偿）将由计算机化的 数据库一年其他重要成果将由 一年后的随访访谈（功能状态、工作状态）和 计算机化记录（工作状况、工资状况）。多因素生存分析 在风险维度内和跨风险维度将用于开发主要风险 模型，包括对损伤严重程度的调整。的可靠性 还将根据医疗记录确定严重程度（具体 目标2）。本研究的第三个目的是制定一个简短的风险评估 下背部和CTS损伤的仪器，这将是有用的， 医生首先治疗受伤的工人。其中的主要焦点 这些文书将涉及那些可以改变的风险因素， 可以接受早期干预以防止残疾。统计 针对这一目的的分析将集中在特异性抗体的敏感性和特异性上。 风险因素的组合。这些风险评估工具将作为试点 在参与职业卫生保健质量的医生中进行测试 改进项目。本项目的第四个目标是确定再伤害 原始下背部损伤队列2中再损伤的发生率和预测因素 在最初受伤的几年后。华盛顿独特的学习环境 包括进行人口抽样的能力， 访问调查受伤工人，医疗，索赔和工作状态的联系 数据库，以及来自商业和劳工团体的支持，将 为这项研究的成功做出了巨大贡献。